neural network signal processing
Research on Computer Digital Signal Processing Network based on the RBF Neural Network
... In this experiment, we used the relate sound card and a mono microphone for 50 young men with sound acquisition. Everyone is a “school” pronunciation of the word, 20 times per person, 15 times for the training, and the ...
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Signal processing and neural network techniques used in Cochlear Implant for different types of noises
... The PET method is used in terms of identification of brain areas that are activated in Quiet, Speech, Noise, SPIN listening conditions irrespective of gender and ear effects and also tells about the activation of complex ...
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Sound Signal Processing with Seq2Tree Network
... a signal and noise separation ...deep neural networks and applied to build tree-strutured LSTMs, however tree-structured LSTMs have not been ap- plied to syntactic ...Deep neural networks have also ...
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II.M ETHODOLOGY A. Vibration Detection
... using neural network and newest digital signal processing techniques, automatically detects noisy sinusoidal vibration parameters of a cantilever beam and generates control signals to an ...
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A REAL TIME QRS DETECTION SYSTEM USED ERROR BACK PROPAGATION NEURAL NETWORK
... real-time signal processing technique adopting a fast Error Back Propagation Neural Network (EBP-NN) algorithm for QRS complex locations is ...the signal then we detected the QRS ...
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A Study on Neural Network in Image Processing
... the neural networks in image processing. Image Processing system includes treating images as two dimensional signals while applying already set signal processing methods to ...of ...
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Feature extraction and classification of heart sound using 1D convolutional neural networks
... other network structures are 2D. At present, when processing a 1D signal with CNNs, the 1D signal is usually mapped to a 2D space (for example, a 1D speech signal can be converted into ...
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A Neural Network MLSE Receiver Based on Natural Gradient Descent: Application to Satellite Communications
... held an Assistant Professor position at INPT (1996–1996). In 2000, he has joined the Department of Electrical and Computer Engi- neering, Queen’s University, Kingston, Canada, where he is now an Associate Professor. Dr. ...
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Radar Signal Detection In Non-Gaussian Noise Using RBF Neural Network
... of signal processing and its applica- ...art signal and image processing problems faced by Indian ...are signal and image processing, multimedia communication, wireless sensor ...
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Neural Network Based Time Delay Estimation
... NNs were utilized, for the first time, in estimating constant time delay. The NNs were trained by the filtered noisy and delayed signal and the noise-free signal. Accurate time-delay estimates were obtained ...
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Mixed-Signal Neural Network Implementation with Programmable Neuron
... the neural network ...the neural network realization is that the design should be able to perform the parallel computation to follow the network principles ...in neural ...
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A Neural Network Approach for ECG Classification
... Thus, neural networks have emerged as a significant classification ...renders neural network classifiers suitable for such ...used signal in clinical practice and one of the first signals ...
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The use of adversaries for optimal neural network training
... results. When looking at the continuum ∆ E distributions for di ff erent NN slices, the distri- bution is sculpted to be more signal-like as NN increases. On the flip side, for a low NN the distribution shows the ...
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Title: CLASSIFICATION ON BREAST CANCER USING GENETIC ALGORITHM TRAINED NEURAL NETWORK
... The neural system is arranged into hidden layers, input and output of the Artificial Neural Networks (ANNs). The neurons are joined together by a series of synaptic weights. An ANN is a powerful tool for ...
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Convolutional neural networks for radar HRRP target recognition and rejection
... Besides the recognition, outlier rejection is another func- tion we have to concern in the RATR system. Thus, to integrate the outlier rejection task into our model, we introduce a decoder network, which focuses ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks become ap- parent only for large-scale problems, which are computationally intensive and not feasible for hand ...MATLAB, neural network al- gorithms can be quickly implemented, ...
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An Efficient Feature Extraction Method with Pseudo Zernike Moment in RBF Neural Network Based Human Face Recognition System
... Face recognition systems should be capable of recogniz- ing face appearances in a changing environment. Therefore we use PZMI to generate the feature vector elements [14, 15]. Also the feature extractor should create a ...
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Molecular Computing with Artificial Neurons
... Figure 5: Pattern grouping with MDH as illustrated by XOR task. The three distinguishable input pat- terns are grouped into two output categories de- pending on whether the amount of product formed is above or below the ...
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The Application of Neural Network in the Technology of Image Processing
... the neural network with the 1089 X×Y×Z data ...the network, and the Z is the training target. Train the network 100 ....Then,the neural network store the information of the map ...
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A Multithreaded CGRA for Convolutional Neural Network Processing
... multithreaded processing in CGRA are proven, and the practical and quantitative methods for building/using multithreaded CGRA neural net- work accelerators are ...
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